| Autor: |
Fuh, Duu-Tong, Luo, Ching-Hsing, Fuh, D T, Luo, C H |
| Předmět: |
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| Zdroj: |
Journal of Medical Engineering & Technology; May/Jun2001, Vol. 25 Issue 3, p118-123, 6p, 2 Diagrams, 4 Charts, 4 Graphs |
| Abstrakt: |
A Morse code auto-recognition system is limited by stable typing speed and stable typing ratio from long to short intervals. For an unstable Morse code typing pattern, the auto-recognition algorithms in the literature are not good enough for applications. This paper adopted a neural network to recognize unstable Morse codes. From an experiment on a teenager with cerebral palsy, the neural network has an average recognition rate up to 93.2%. The recognition rate from an amputee aged 40, who used a prosthesis for typing, it is 97.2% on average. When we compare this to 99.2% for the recognition rate from a skilled expert, the result is quite promising. The neural network has successfully overcome the difficulty of analysing a severely unstable Morse code time series. Since the human typing speed is quite slow in comparison to signal processing by the computer, it also makes it possible to use a neural network for real-time signal recognition. [ABSTRACT FROM AUTHOR] |
| Databáze: |
Complementary Index |
| Externí odkaz: |
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